Refactor online recognizer (#250)

* Refactor online recognizer.

Make it easier to support other streaming models.

Note that it is a breaking change for the Python API.
`sherpa_onnx.OnlineRecognizer()` used before should be
replaced by `sherpa_onnx.OnlineRecognizer.from_transducer()`.

sherpa-onnx/python/sherpa_onnx/online_recognizer.py

@@ -5,6 +5,7 @@ from typing import List, Optional
 from _sherpa_onnx import (
     EndpointConfig,
     FeatureExtractorConfig,
+    OnlineModelConfig,
     OnlineRecognizer as _Recognizer,
     OnlineRecognizerConfig,
     OnlineStream,
@@ -24,8 +25,9 @@ class OnlineRecognizer(object):
      - https://github.com/k2-fsa/sherpa-onnx/blob/master/python-api-examples/online-decode-files.py
     """
 
-    def __init__(
-        self,
+    @classmethod
+    def from_transducer(
+        cls,
         tokens: str,
         encoder: str,
         decoder: str,
@@ -95,6 +97,7 @@ class OnlineRecognizer(object):
             Online transducer model type. Valid values are: conformer, lstm,
             zipformer, zipformer2. All other values lead to loading the model twice.
         """
+        self = cls.__new__(cls)
         _assert_file_exists(tokens)
         _assert_file_exists(encoder)
         _assert_file_exists(decoder)
@@ -102,10 +105,14 @@ class OnlineRecognizer(object):
 
         assert num_threads > 0, num_threads
 
-        model_config = OnlineTransducerModelConfig(
-            encoder_filename=encoder,
-            decoder_filename=decoder,
-            joiner_filename=joiner,
+        transducer_config = OnlineTransducerModelConfig(
+            encoder=encoder,
+            decoder=decoder,
+            joiner=joiner,
+        )
+
+        model_config = OnlineModelConfig(
+            transducer=transducer_config,
             tokens=tokens,
             num_threads=num_threads,
             provider=provider,
@@ -135,6 +142,7 @@ class OnlineRecognizer(object):
 
         self.recognizer = _Recognizer(recognizer_config)
         self.config = recognizer_config
+        return self
 
     def create_stream(self, contexts_list: Optional[List[List[int]]] = None):
         if contexts_list is None: